A Mobile Sensing and Imaging System for Real-Time Monitoring of Spine Health

Abstract

Poor posture or extra stress on the spine has been shown to lead to a variety of spinal disorders including chronic back pain, and to incur numerous health costs to society. For this reason, workplace ergonomics is rapidly becoming indispensable in all major corporations. Making the individual continuously aware of poor posture may reduce out-of-posture tendencies and encourage healthy spinal habits. Spine stress can also worsen existing structural deformities in the spine such as adolescent idiopathic scoliosis (AIS). In this work we developed a system to monitor spine health through both dynamic monitoring and structural imaging. The dynamic sensing method monitors spine stress in realtime by detecting poor back posture and strain on the back due to prolonged sitting or standing, and provides real-time user feedback when poor posture is sustained. The imaging method extracts the structural curvature of the spine and is used for the diagnosis of AIS in a non-invasive and inexpensive manner. Namely, the image is obtained using a photograph where the spinous processes have been marked to trace the shape of the spine. The spine curvature is then extracted automatically and modeled by a curve-fitting polynomial. The approach is simple and practical and allows scoliosis patients to monitor their curvature progress from home while minimizing the use of x-rays. The theme of our work is spine health, which we monitor through the wireless sensing system and the orthopedic imaging system. The two are complementary: the mobile wireless system assesses spine health during daily activity while the imaging system can assess the progression of a patient’s structural spine curvature. We demonstrate effectiveness of our sensing system in simultaneously monitoring posture and position by testing in numerous situations. Furthermore, experiments show that our imaging method is accurate and robust under different brightness conditions. X-ray data used for this study was obtained from the international, electronic database of surgical cases of AIS, Scolisoft®.